In this paper we determine the fusion rules of the logarithmic Wp,q triplet theory and construct the Grothendieck group with subgroups for which consistent product structures can be defined. The fusion rules are then used to determine projective covers. This allows us also to write down a candidate for a modular invariant partition function. Our results demonstrate that recent work on the W2,3 ...

In this paper the behavior of three combinational rules for temporal/sequential attribute data fusion for target type estimation are analyzed. The comparative analysis is based on: Dempster’s fusion rule proposed in Dempster-Shafer Theory; Proportional Conflict Redistribution rule no. 5 (PCR5), proposed in Dezert-Smarandache Theory and one alternative class fusion rule, connecting the combinati...

In medical application the multimodal image fusion is an important tool. It has developed with the advent of various imaging modalities in medical imaging. It is mostly used for the medical diagnosis. In this proposal a novel fusion technique is proposed for the multi modal medical image based on the NSCT (non-sub sampled Contourlet transform). In this algorithm high frequency and low frequency...

In this paper we tackle distributed detection of a non-cooperative target with a Wireless Sensor Network (WSN). When the target is present, sensors observe an unknown random signal with amplitude attenuation depending on the distance between the sensor and the target (unknown) positions, embedded in white Gaussian noise. The Fusion Center (FC) receives sensors decisions through error-prone Bina...

The (p+, p−) singlet algebra is a vertex operator algebra that is strongly generated by a Virasoro field of central charge 1− 6(p+− p−) /p+p− and a single Virasoro primary field of conformal weight (2p+−1)(2p−−1). Here, the modular properties of the characters of the uncountably many simple modules of each singlet algebra are investigated and the results used as the input to a continuous analog...

Profound theoretical analysis is performed of small-sample properties of trainable fusion rules to determine in which situations neural network ensembles can improve or degrade classification results. We consider small sample effects, specific only to multiple classifiers system design in the two-category case of two important fusion rules: (1) linear weighted average (weighted voting), realize...

With this chapter we aims at describing several basic aspects of matching score level fusion. Section 14.1 provides a description of basic characteristics of matching score fusion in the form of introduction. Section 14.2 shows a number of matching score fusion rules. Section 14.3 surveys several typical normalization procedures of raw matching scores. Section 14.4 gives an example of matching ...

We consider a generalized form of the conventional decentralized control architecture for discrete-event systems where the control actions of a set of supervisors can bè`fused'' using both union and intersection of enabled events. Namely, the supervisors agree a priori on choosing``fusion by union'' for certain controllable events and``fusion by intersection'' for certain other controllable eve...

Data fusion is the process of combining multiple representations of the same object, extracted from several external sources, into a single and clean representation. It is usually the last step of an integration process, which is executed after the schema matching and the entity identification steps. More specifically, data fusion aims at solving attribute value conflicts based on user-defined ...